A little Python, some neural network command line work, and the blog can start posting computer-generated wine reviews

Sooner rather than later, I’m going to post computer-generated wine reviews on the blog. Thanks to the Lifehacker website, all I need are some basic Python programing skills. Or, even better, find a Python-savvy volunteer from among the blog’s sophisticated and erudite audience who wants to help “write” them.

The point here? That wine has become so mechanized and so predictable that we can probably get acceptable Winestream Media-style reviews from an artificial intelligence. It’s probably even possible to teach the machine to give scores – a delicious irony that is reason enough to make this work.

Lifehacker’s Beth Skawrecki writes that machine-written reviews are more possible than ever thanks to advances in neural networks. A neural network is “a type of [artificial intelligence] modeled on the network-like nature of our own brains. You train a neural network by giving it input: recipes, for example. The network strengthens some of the connections between its neurons (imitation brain cells) more than others as it learns. The idea is that it’s figuring out the rules of how the input works: which letters tend to follow others, for example. Once the network is trained, you can ask it to generate its own output, or to give it a partial input and ask it to fill in the rest.”

For our purposes, we would tell the computer what chardonnay is supposed to taste like, where the grapes were grown, information about the vintage and the winemaker’s style, and the price. Then, we can “teach” it to interpret that information to write the review – that chardonnay from California is different in certain ways from chardonnay from France, for example.

“Wine drinkers want to be reassured that what they are drinking is worth what they paid for it. That’s the goal of the post-modern wine business and premiumization, and I was created to do that.”

Computer-generated wine writing has arrived, if this interview is any indication. I talked to Arty, the world’s first artificial intelligence wine writer, for this edition of the podcast.

Arty and I discussed why he was created, his goal as a critic — “We’ll always need quality wine writing, human or otherwise. But I think I can offer consumers wine criticism that they can’t get anywhere else” — and why his kind may be the future.

Could artificial intelligence make writers obsolete? Because I’m not the only one who wonders. Barbara Ehrenreich, writing in the New York Times, firmly believes that “the business of book reviewing could itself be automated and possibly improved by computers.”

So why not wine writing — computer-generated wine reviews?

This would solve any number of problems, not the least of which is that winemakers wouldn’t have to deal with people like me. I had a brief email discussion recently with an annoyed producer who insisted that her wines didn’t taste the way I described them; she certainly would have been better off with WineNet than what Ehrenreich calls a “wet, carbon-based thinking apparatus” with self-awareness and a sense of obligation to its readers.

The last time I wrote about this, a company called Narrative Science had made significant inroads in taking disparate facts and turning them into a readable narrative. Unfortunately, it seems to have veered elsewhere, developing a product that “creates new revenue opportunities by transforming data into engaging content that can be productized and monetized.” This approach has little to do with writing, since there is money involved.

Still, much work has been done. TechCrunch reported last month that robot writers are all the rage in Silicon Valley, while a data scientist named Tony Fischetti has written that Markov chains can be used to simulate what he calls the “exercise in pretentiousness” that is a wine review. The concept of a Markov chain, which deals with probability, is far beyond my math skills, but Fischetti used 9,000 reviews from the Wine Spectator to write a program that came up with tasting notes that are no worse than most, including: “Quite rich, but stopping short of opulent, this white sports peach and apricot, yet a little in finesse” and “this stylish Australian Cabernet is dark, deep and complex, ending with a polished mouthful of spicy fruit and plenty of personality.”

Meanwhile, a wine producer in France, using N-Gram analysis (also beyond my math skills, but apparently related to word order) also thinks it’s possible to generate wine reviews without a wine writer. Both approaches seem to jive with what I wrote last time, that an artificial intelligence, working with a wine term database and the proper algorithm, could scrape together effective reviews. Probably even scores, too.

I just hope, if and when this puts me out of business, that someone will remember that I saw it coming. Maybe I can monetize the blog that way.